data <- readRDS(paste0(wd, "RDS/Data_Objects/all_data.rds"))
pcaObj <- pca(data$dfs$lipids)
plot1 <- plotIndiv(pcaObj,
ind.names= data$samples$names,
group = data$samples$group,
legend = TRUE,
legend.title = 'Group',
title = "",
col = Group.Palette)$graph
plot2 <- plotIndiv(pcaObj,
group = data$samples$group,
pch = data$samples$sex,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Sex',
title = "",
col = Group.Palette)$graph
plot3 <- plotIndiv(pcaObj,
group = data$samples$group,
pch = data$samples$race,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Race',
title = "",
col = Group.Palette)$graph
plot4 <- plotIndiv(pcaObj,
group = data$samples$group,
pch = data$samples$ageDisc,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Age',
title = "",
col = Group.Palette)$graph
Plot_Grid(list(plot1, plot2,
plot3, plot4))
Supp. Figure 1
pcaObj <- pca(data$dfs$proteins)
plot1 <- plotIndiv(pcaObj,
ind.names= data$samples$names,
group = data$samples$group,
legend = TRUE,
legend.title = 'Group',
title = "",
col = Group.Palette)$graph
plot2 <- plotIndiv(pcaObj,
group = data$samples$group,
pch = data$samples$sex,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Sex',
title = "",
col = Group.Palette)$graph
plot3 <- plotIndiv(pcaObj,
group = data$samples$group,
pch = data$samples$race,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Race',
title = "",
col = Group.Palette)$graph
plot4 <- plotIndiv(pcaObj,
group = data$samples$group,
pch = data$samples$ageDisc,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Age',
title = "",
col = Group.Palette)$graph
Plot_Grid(list(plot1, plot2,
plot3, plot4))
Supp. Figure 2
plsdaObj <- plsda(data$dfs$lipids,
data$samples$group,,
scale=T)
plot1 <- plotIndiv(plsdaObj,
ind.names= data$samples$names,
group = data$samples$group,
legend = TRUE,
legend.title = 'Group',
title = "",
col = Group.Palette)$graph
plot2 <- plotIndiv(plsdaObj,
group = data$samples$group,
pch = data$samples$sex,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Sex',
title = "",
col = Group.Palette)$graph
plot3 <- plotIndiv(plsdaObj,
group = data$samples$group,
pch = data$samples$race,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Race',
title = "",
col = Group.Palette)$graph
plot4 <- plotIndiv(plsdaObj,
group = data$samples$group,
pch = data$samples$ageDisc,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Age',
title = "",
col = Group.Palette)$graph
Plot_Grid(list(plot1, plot2,
plot3, plot4))
Supp. Figure 3
plsdaObj <- plsda(data$dfs$proteins,
data$samples$group,,
scale=T)
plot1 <- plotIndiv(plsdaObj,
ind.names= data$samples$names,
group = data$samples$group,
legend = TRUE,
legend.title = 'Group',
title = "",
col = Group.Palette)$graph
plot2 <- plotIndiv(plsdaObj,
group = data$samples$group,
pch = data$samples$sex,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Sex',
title = "",
col = Group.Palette)$graph
plot3 <- plotIndiv(plsdaObj,
group = data$samples$group,
pch = data$samples$race,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Race',
title = "",
col = Group.Palette)$graph
plot4 <- plotIndiv(plsdaObj,
group = data$samples$group,
pch = data$samples$ageDisc,
legend = TRUE,
legend.title = 'Group',
legend.title.pch = 'Age',
title = "",
col = Group.Palette)$graph
Plot_Grid(list(plot1, plot2,
plot3, plot4))
Supp. Figure 4
data <- readRDS(paste0(wd, "RDS/Data_Objects/all_data.rds"))
lipidsReduced <- Remove_Intercorrelated_Features(data$dfs$lipids, 0.85)
plot1 <- (plsda(data$dfs$lipids, data$samples$group, scale=T) %>%
plotIndiv(group = data$samples$group,
ind.names=F))[["graph"]]
plot2 <- (plsda(lipidsReduced, data$samples$group, scale=T) %>%
plotIndiv(group = data$samples$group,
ind.names=F))[["graph"]]
Plot_Grid(list(plot1, plot2))
Supp. Figure 5
proteinsReduced <- Remove_Intercorrelated_Features(data$dfs$proteins, 0.7)
plot1 <- (plsda(data$dfs$proteins, data$samples$group, scale=T) %>%
plotIndiv(group = data$samples$group,
ind.names=F))[["graph"]]
plot2 <- (plsda(proteinsReduced, data$samples$group, scale=T) %>%
plotIndiv(group = data$samples$group,
ind.names=F))[["graph"]]
Plot_Grid(list(plot1, plot2))
Supp. Figure 6
data <- readRDS(paste0(wd, "RDS/Data_Objects/engineered_data.rds"))
plsdaObj <- plsda(data$dfs$engineered,
data$samples$group)
plotLoadings(plsdaObj,
comp=1,
contrib = 'max',
method = 'median',
ndisplay = 25)
Supp. Figure 7
plotLoadings(plsdaObj,
comp=2,
contrib = 'max',
method = 'median',
ndisplay = 25)
Supp. Figure 8
data <- readRDS(paste0(wd, "RDS/Data_Objects/engineered_data.rds"))
lipidPCA <- pca(data$dfs$lipids,
scale=T)
plotIndiv(lipidPCA,
ind.names= data$samples$names,
group = data$samples$group,
legend = TRUE,
legend.title = 'Group',
title = "Filtered lipid PCA",
col = Group.Palette)
Supp. Figure 9
proteinPCA <- pca(data$dfs$proteins,
scale=T)
plotIndiv(proteinPCA,
ind.names= data$samples$names,
group = data$samples$group,
legend = TRUE,
legend.title = 'Group',
title = "Filtered protein PCA",
col = Group.Palette)
Supp. Figure 10
engineeredPCA <- pca(data$dfs$engineered,
scale=T)
plotIndiv(engineeredPCA,
ind.names= data$samples$names,
group = data$samples$group,
legend = TRUE,
legend.title = 'Group',
title = "Engineered PCA",
col = Group.Palette)
Supp. Figure 10
model <- readRDS(paste0(wd, "RDS/final_model.rds"))
auroc(model, roc.comp = 1, roc.block = 1)
Supp. Figure 11
auroc(model, roc.comp = 1, roc.block = 2)
Supp. Figure 12
auroc(model, roc.comp = 1, roc.block = 3)
Supp. Figure 13
plotLoadings(model,
comp = 2,
contrib = 'max',
method = 'median',
ndisplay = 20) %>% suppressMessages()
Supp. Figure 14